SOTAVerified

Few-Shot Semantic Segmentation

Few-shot semantic segmentation (FSS) learns to segment target objects in query image given few pixel-wise annotated support image.

Papers

Showing 125 of 168 papers

TitleStatusHype
SegGPT: Segmenting Everything In ContextCode4
FAMNet: Frequency-aware Matching Network for Cross-domain Few-shot Medical Image SegmentationCode2
Label Anything: Multi-Class Few-Shot Semantic Segmentation with Visual PromptsCode2
Matcher: Segment Anything with One Shot Using All-Purpose Feature MatchingCode2
Learning What Not to Segment: A New Perspective on Few-Shot SegmentationCode2
Language-driven Semantic SegmentationCode2
Few-shot Structure-Informed Machinery Part Segmentation with Foundation Models and Graph Neural NetworksCode1
AFANet: Adaptive Frequency-Aware Network for Weakly-Supervised Few-Shot Semantic SegmentationCode1
Lightweight Frequency Masker for Cross-Domain Few-Shot Semantic SegmentationCode1
Bridge the Points: Graph-based Few-shot Segment Anything SemanticallyCode1
Unleashing the Potential of the Diffusion Model in Few-shot Semantic SegmentationCode1
Hybrid Mamba for Few-Shot SegmentationCode1
MSDNet: Multi-Scale Decoder for Few-Shot Semantic Segmentation via Transformer-Guided PrototypingCode1
Generalized Few-Shot Semantic Segmentation in Remote Sensing: Challenge and BenchmarkCode1
Small Object Few-shot Segmentation for Vision-based Industrial InspectionCode1
Eliminating Feature Ambiguity for Few-Shot SegmentationCode1
Few-Shot Medical Image Segmentation with High-Fidelity PrototypesCode1
Label-Efficient Semantic Segmentation of LiDAR Point Clouds in Adverse Weather ConditionsCode1
Cross-Domain Few-Shot Semantic Segmentation via Doubly Matching TransformationCode1
Learnable Prompt for Few-Shot Semantic Segmentation in Remote Sensing DomainCode1
Domain-Rectifying Adapter for Cross-Domain Few-Shot SegmentationCode1
A Novel Benchmark for Few-Shot Semantic Segmentation in the Era of Foundation ModelsCode1
Self-Calibrated Cross Attention Network for Few-Shot SegmentationCode1
Self-supervised Few-shot Learning for Semantic Segmentation: An Annotation-free ApproachCode1
DifFSS: Diffusion Model for Few-Shot Semantic SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SegGPT (ViT)Mean IoU83.2Unverified
2DCAMA (ResNet-101)FB-IoU77.6Unverified
3PGMA-Net (ResNet-101)Mean IoU77.6Unverified
4PGMA-Net (ResNet-50)Mean IoU74.1Unverified
5PGMA-Net (ViT-B/16)Mean IoU74.1Unverified
6GF-SAM (DINOv2)Mean IoU72.1Unverified
7HMNet (ResNet-50)Mean IoU70.4Unverified
8AENet (ResNet-50)Mean IoU70.3Unverified
9HDMNet (DifFSS, ResNet-50)Mean IoU70.2Unverified
10VAT + MSI (ResNet-101)Mean IoU70.1Unverified
#ModelMetricClaimedVerifiedStatus
1SegGPT (ViT)Mean IoU89.8Unverified
2GF-SAM (DINOv2)Mean IoU82.6Unverified
3PGMA-Net (ResNet-101)Mean IoU78.6Unverified
4FPTrans (DeiT-B/16)Mean IoU78Unverified
5DGPNet (ResNet-101)Mean IoU75.4Unverified
6PGMA-Net (ResNet-50)Mean IoU75.2Unverified
7DCAMA (Swin-B)Mean IoU74.9Unverified
8PGMA-Net (ViT-B/16)Mean IoU74.6Unverified
9AENet (ResNet-50)Mean IoU74.2Unverified
10HMNet (ResNet-50)Mean IoU74.1Unverified